publications

2024

1. Estimating flexibility preferences to resolve temporal scheduling conflicts in activity-based modelling

   Patrick Manser, Tom Haering, Tim Hillel, Janody Pougala, Rico Krueger, and Michel Bierlaire

   Transportation, Apr 2024

   Abs DOI

   This paper presents a novel activity-based demand model that combines an optimisation framework for continuous temporal scheduling decisions (i.e. activity timings and durations) with traditional discrete choice models for non-temporal choice dimensions (i.e. activity participation, number and type of tours, and destinations). The central idea of our approach is that individuals resolve temporal scheduling conflicts that arise from overlapping activities, e.g. needing to work and desiring to shop at the same time, in order to maximise their daily utility. Flexibility parameters capture behavioural preferences that penalise deviations from desired timings. This framework has three advantages over existing activity-based modelling approaches: (i) the time conflicts between different temporal scheduling decisions including the activity sequence are treated jointly; (ii) flexibility parameters follow a utility maximisation approach; and (iii) the framework can be used to estimate and simulate a city-scale case study in reasonable time. We introduce an estimation routine that allows flexibility parameters to be estimated using real-world observations as well as a simulation routine to efficiently resolve temporal conflicts using an optimisation model. The framework is applied to the full-time workers of a synthetic population for the city of Lausanne, Switzerland. We validate the model results against reported schedules. The results demonstrate the capabilities of our approach to reproduce empirical observations in a real-world case study.

2. Joint Modelling of Electric Vehicle Charging and Daily Activity Scheduling

   Senlei Wang, Janody Pougala, and Tim Hillel

   Available at SSRN 5143388, Apr 2024
3. What we learned so far with E-Bike City Research D-BAUG Lighthouse Project

   Catherine Elliot, Kay W. Axhausen, Alessio Daniele Marra, Florian Fuchs, Francesco Corman, Lukas Ballo, Clarissa Livingston, Milos Balac, Ying-Chuan Ni, and Michail Makridis

   In IVT Seminar, Apr 2024

2023

1. OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

   Janody Pougala, Tim Hillel, and Michel Bierlaire

   Transportation Research Part C: Emerging Technologies, Oct 2023

   Abs DOI

   Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between subsequent choices, oversimplifying the scheduling process. In this paper we introduce OASIS, an integrated framework to simulate activity schedules by considering all choice dimensions simultaneously. We present a methodology for the estimation of the parameters of an activity-based model from historic data, allowing for the generation of realistic and consistent daily mobility schedules. The estimation process has two main elements: (i) choice set generation, using the Metropolis-Hasting algorithm, and (ii) estimation of the maximum likelihood estimators of the parameters. We test our approach by estimating parameters of multiple utility specifications for a sample of individuals from a Swiss nationwide travel survey, and evaluating the output of the OASIS model against realised schedules from the data. The results demonstrate the ability of the new framework to simulate realistic distributions of activity schedules, and estimate stable and significant parameters from historic data that are consistent with behavioural theory. This work opens the way for future developments of activity-based models, where a great deal of constraints can be explicitly included in the modelling framework, and all choice dimensions are handled simultaneously.

2022

1. Capturing trade-offs between daily scheduling choices

   Janody Pougala, Tim Hillel, and Michel Bierlaire

   Journal of Choice Modelling, Jun 2022

   Abs DOI

   We propose a new modelling approach for daily activity scheduling which integrates the different daily scheduling choice dimensions (activity participation, location, schedule, duration and transportation mode) into a single optimisation problem. The fundamental behavioural principle behind our approach is that individuals schedule their day to maximise their overall derived utility from the activities they complete, according to their individual needs, constraints, and preferences. By combining multiple choices into a single optimisation problem, our framework is able to capture the complex trade-offs between scheduling decisions for multiple activities. These trade-offs could include how spending longer in one activity will reduce the time-availability for other activities or how the order of activities determines the travel-times. The implemented framework takes as input a set of considered activities, with associated locations and travel modes, and uses these to produce empirical distributions of individual schedules from which different daily schedules can be drawn. The model is illustrated using historic trip diary data from the Swiss Mobility and Transport Microcensus. The results demonstrate the ability of the proposed framework to generate complex and realistic distributions of starting time and duration for different activities within the tight time constraints. The generated schedules are then compared to the aggregate distributions from the historical data to demonstrate the feasibility and flexibility of our approach.